Pressure-Bearing Parameter Identification for Martian Soil Based on a Terramechanics Model and Genetic Algorithm
Publication: Journal of Aerospace Engineering
Volume 31, Issue 2
Abstract
A wheel-terrain interaction mechanics model based on terramechanics and simplified force and moment reconstruction is introduced. The model comprises pressure-bearing parameters (combined deformation modulus and slip sinkage exponent), wheel load, driving torque, slip ratio, and wheel sinkage. A genetic algorithm is used to identify the pressure-bearing parameters using a calibration dataset. Experiments were performed on the calibration dataset and a prediction dataset using a single-wheel soil bin to measure the driving torque, wheel sinkage, and drawbar pull of a griddle net wheel under different slip ratios. The proposed model comprises two processes. The first process is to determine the slip sinkage exponent using its empirical value to estimate the combined deformation modulus, and the second is to correct the slip sinkage exponent in which the value of the combined deformation modulus is fixed. The prediction dataset was used to validate the model, with the wheel sinkage and drawbar pull calculated using the wheel-terrain interaction mechanics model with the identified pressure-bearing parameters. The correlation coefficients of the predicted and measured values of the wheel sinkage and drawbar pull were 0.9712 and 0.8902, respectively. An additional experiment was performed with a continuous slip ratio ranging from 0.16 to 0.7 and a wheel load of 50 N to validate the proposed model, and the correlation coefficient between the predicted and measured wheel sinkage was 0.9660. The experimental results demonstrate that the genetic algorithm is able to accurately predict the pressure-bearing parameters, which can be used for traversability prediction, risk assessment, and automatic path planning.
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Acknowledgments
The authors thank the anonymous reviewers for their critical and constructive review of the manuscript. This study was cosupported by the National Natural Science Foundation of China (Nos. 51375199 and 51775233), Pre-Research Foundation of Institute of Spacecraft System Engineering (No. 5010120151026), and National Defense Pre-Research Foundation of Jilin University (No. JDXJY20130207).
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Published In
Journal of Aerospace Engineering
Volume 31 • Issue 2 • March 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Nov 9, 2016
Accepted: Jul 28, 2017
Published online: Dec 22, 2017
Published in print: Mar 1, 2018
Discussion open until: May 22, 2018
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